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A Multi-tiered Recommender System Architecture for Supporting E-Commerce

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Part of the Studies in Computational Intelligence book series (SCI,volume 446)

Abstract

Nowadays, many e-Commerce tools support customers with automatic recommendations. Many of them are centralized and lack in efficiency and scalability, while other ones are distributed and require a computational overhead excessive for many devices. Moreover, all the past proposals are not “open” and do not allow new personalized terms to be introduced into the domain ontology. In this paper, we present a distributed recommender, based on a multi-tiered agent system, trying to face the issues outlined above. The proposed system is able to generate very effective suggestions without a too onerous computational task. We show that our system introduces significant advantages in terms of openess, privacy and security.

Keywords

  • Recommender System
  • Collaborative Filter
  • Auction Site
  • Seller Agent
  • Broker Agent

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Luigi Palopoli .

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Palopoli, L., Rosaci, D., Sarné, G.M.L. (2013). A Multi-tiered Recommender System Architecture for Supporting E-Commerce. In: Fortino, G., Badica, C., Malgeri, M., Unland, R. (eds) Intelligent Distributed Computing VI. Studies in Computational Intelligence, vol 446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32524-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-32524-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

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